libpyhat.IO package

Submodules

libpyhat.IO.cube_to_df module

libpyhat.IO.cube_to_df.cube_to_df(cube, wvls, spect_label='wvl', meta_label='meta')

libpyhat.IO.cube_to_df.df_parameter_to_2d(df, parameter_name, meta_label='meta', shape_2d=None)

libpyhat.IO.cube_to_df.df_to_cube(df, spect_label='wvl', meta_label='meta', cube_shape=None)

libpyhat.IO.io_ccam_pds module

libpyhat.IO.io_ccam_pds.CCAM_CSV(input_data, ave=True)

libpyhat.IO.io_ccam_pds.CCAM_SAV(input_data, ave=True)

libpyhat.IO.io_ccam_pds.ccam_batch(directory, searchstring='*ccs*.csv', to_csv=None, ave=True, versioncheck=True, data_name='ChemCam', to_pickle=False, outpath='', outfile=None)

libpyhat.IO.io_cube module

libpyhat.IO.io_cube.read(f)

libpyhat.IO.io_kaguya_sp module

libpyhat.IO.io_kaguya_sp.spectral_profiler(f)

Generate DataFrame from spectral profiler data.

parameters

fstr

file path to spectral profiler file

libpyhat.IO.io_supercam_pds module

libpyhat.IO.io_supercam_pds.read_supercam_fits(i, filelist, shot_to_shot, headerkeys)

libpyhat.IO.io_supercam_pds.supercam_batch(searchdirs, searchstring='*cl1*.fits', headerkeys=None, shot_to_shot=False, to_csv=False, to_pickle=False, data_name='SuperCam', outpath='', outfile=None)

Module contents